1. Field
This application relates generally to scoring documents, and more specifically to a system and method for scoring documents based on attributes of a digital document by eye-tracking data analysis.
2. Related Art
Eye-tracking systems can be included in many of today's electronic devices such as personal computers, laptops, tablet computers, user-wearable goggles, smart phones, digital billboards, game consoles, and the like. An eye-tracking system may monitor a user as the user engages a digital document (e.g. a static webpage, a dynamic webpage, an e-reader page, a MMS message, a digital billboard content, an augmented reality viewer that can include computer-generated sensory input such as sound, video, graphics or UPS data, a digital photograph or video viewer, and the like). The eye-tracking data (e.g. can include information about a user's eye movement such as regressions, fixation metrics such as time to first fixation and fixation duration, scan paths, gaze plots, fixation patterns, saccade patterns, pupil sizes, blinking patterns and the like) may indicate a coordinate location (such as an x.y coordinate with a time stamp) of a particular visual element of the digital document—such as a particular word in a text field or figure in an image. For instance, a person reading an e-book text may quickly read over some words while pausing at others. Quick eye movements may then be associated with the words the person was reading. When the eyes simultaneously pause and focus on a certain word for a longer duration than other words, this response may then be associated with the particular word the person was reading. This association of a particular word and eye-tracking data of certain parameters may then be analyzed. In this way, eye-tracking data can indicate certain states within the user that are related to the elements of the digital document that correspond to particular eye movement patterns. For example, a particular eye-tracking pattern can be associated with a comprehension difficulty of a word and/or image. Another eye-tracking pattern can indicate a user's interest in a particular image, portion of an image, phrase, etc. A longer duration of gaze upon a visual element may, for example, indicate a greater degree of interest in the element over other elements of a digital document associated with shorter gaze durations.
Eye-tracking data can be collected from a variety of devices and eye-tracking systems. Computing devices frequently include high-resolution cameras capable of monitoring a person's facial expressions and/or eye movements while viewing or experiencing media. Cellular telephones now include high-resolution user-facing cameras, proximity sensors, accelerometers, and gyroscopes and these ‘smart phones’ have the capacity to expand the hardware to include additional sensors. Thus, video-based eye-tracking systems can be integrated into existing electronic devices.
Searches of databases of digital documents (e.g. webpages) have become a common activity of modern life. Typical search engines search for the words or phrases as they are entered in the search query. However, this can be a problem when the entered words have multiple meanings. “Bed,” for example, can be a place to sleep, a place where flowers are planted, the storage space of a truck or a place where fish lay their eggs. One particular meaning may be more relevant to a user's current state, and the other meanings may be irrelevant. A use can build search queries that endeavor to eliminate unwanted meanings, but this process can be time consuming and require multiple trial and error attempts.
Thus, a method and system are desired for using eye-tracking data collected from prolific digital devices to obtain information about a user's state (e.g. interests, comprehension difficulties and the like) as related to elements of a digital document to improve beyond existing methods of sorting other documents according to their relevance to a search query performed by a user.